By Christopher Monckton of Brenchley
A commenter on my post mentioning that according to the RSS satellite monthly global mean surface temperature dataset there has been no global warming at all for 200 months complains that I have cherry-picked my dataset. So let’s pick all the cherries. Here are graphs for all five global datasets since December 1996.
GISS:
HadCRUt4:
NCDC:
RSS:
UAH:
The mean of the three terrestrial datasets:
The mean of the two satellite datasets:
The mean of all five datasets:
Since a trend of less than 0.15 K is within the combined 2 σ data uncertainties arising from errors in measurement, bias, and coverage, global warming since December 1996 is only detectable on the UAH dataset, and then barely. On the RSS dataset, there has been no global warming at all. None of the datasets shows warming at a rate as high as 1 Cº/century. Their mean is just 0.5 Cº/century.
The bright blue lines are least-squares linear-regression trends. One might use other methods, such as order-n auto-regressive models, but in a vigorously stochastic dataset with no detectable seasonality the result will differ little from the least-squares trend, which even the IPCC uses for temperature trend analysis.
The central question is not how long there has been no warming, but how wide is the gap between what the models predict and what the real-world weather brings. The IPCC’s Fifth Assessment Report, to be published in Stockholm on September 27, combines the outputs of 34 climate models to generate a computer consensus to the effect that from 2005-2050 the world should warm at a rate equivalent to 2.33 Cº per century. Yeah, right. So, forget the Pause, and welcome to the Gap:
GISS:
HadCRUt4:
NCDC:
RSS:
UAH:
Mean of all three terrestrial datasets:
Mean of the two satellite datasets (monthly Global Warming Prediction Index):
Mean of all five datasets:
So let us have no more wriggling and squirming, squeaking and shrieking from the paid trolls. The world is not warming anything like as fast as the models and the IPCC have predicted. The predictions have failed. They are wrong. Get over it.
Does this growing gap between prediction and reality mean global warming will never resume? Not necessarily. But it is rightly leading many of those who had previously demanded obeisance to the models to think again.
Does the Great Gap prove the basic greenhouse-gas theory wrong? No. That has been demonstrated by oft-repeated experiments. Also, the fundamental equation of radiative transfer, though it was discovered empirically by Stefan (the only Slovene after whom an equation has been named), was demonstrated theoretically by his Austrian pupil Ludwig Boltzmann. It is a proven result.
The Gap is large and the models are wrong because in their obsession with radiative change they undervalue natural influences on the climate (which might have caused a little cooling recently if it had not been for greenhouse gases); they fancifully imagine that the harmless direct warming from a doubling of atmospheric CO2 concentration – just 1.16 Cº – ought to be tripled by imagined net-positive temperature feedbacks (not one of which can be measured, and which in combination may well be net-negative); they falsely triple the 1.16 Cº direct warming on the basis of a feedback-amplification equation that in its present form has no physical meaning in the real climate (though it nicely explains feedbacks in electronic circuits, for which it was originally devised); they do not model non-radiative transports such as evaporation and convection correctly (for instance, they underestimate the cooling effect of evaporation threefold); they do not take anything like enough account of the measured homeostasis of global temperatures over the past 420,000 years (variation of little more than ±3 Cº, or ±1%, in all that time); they daftly attempt to overcome the Lorentz unpredictability inherent in the mathematically-chaotic climate by using probability distributions (which, however, require more data than straightforward central estimates flanked by error-bars, and are thus even less predictable than simple estimates); they are aligned to one another by “inter-comparison” (which takes them further and further from reality); and they are run by people who fear, rightly, that politicians would lose interest and stop funding them unless they predict catastrophes (and fear that funding will dry up is scarcely a guarantee of high-minded, objective scientific inquiry).
That, in a single hefty paragraph, is why the models are doing such a spectacularly awful job of predicting global temperature – which is surely their key objective. They are not fit for their purpose. They are mere digital masturbation, and have made their operators blind to the truth. The modelers should be de-funded. Or perhaps paid in accordance with the accuracy of their predictions. Sum due to date: $0.00.
In the face of mounting evidence that global temperature is not responding at ordered, the paid trolls – one by one – are falling away from threads like this, and not before time. Their funding, too, is drying up. A few still quibble futilely about whether a zero trend is a negative trend or a statistically-insignificant trend, or even about whether I am a member of the House of Lords (I am – get over it). But their heart is not in it. Not any more.
Meanwhile, enjoy what warmth you can get. A math geek with a track-record of getting stuff right tells me we are in for 0.5 Cº of global cooling. It could happen in two years, but is very likely by 2020. His prediction is based on the behavior of the most obvious culprit in temperature change here on Earth – the Sun.
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Who can say the models aren’t wrong? The evidence cannot possibly be more clear. So warmists, scrap the models and go back to the drawing boards! You ain’t got nuthin’.
The “3 degrees” is a strong element of every one of the Gap graphs (as in the oft-quoted 3 degrees of increase for a simple doubling of CO2 concentration). All the graphs are over/predicting by this same 3 degrees, with very minor variations.
This ought to lead to at least a question about the reliability of the sensitivity assumptions behind the models, I’d have thought …
Oh, as for “sum due to date” – I’d argue that they owe us all a few billions already …
So, now the ancient fear is graphically clarified…what “they” used to tell the boys, the caution: wanton digital manipulation leads to blindness. QED. Bravo, Lord Christopher!
If the models are as wrong as they appear to be, and the areas of error are as clear as outlined by Lord Monckton (Title not in doubt by me), has anybody published a more realistic model output that matches reality?
They should surely have the message by now. Excellent post.
To be fair , and as with both sides , ‘paid trolls ‘ is not really an issue like all religions the most fanatical are volunteers whose motivation is many fold but not finical . And we should be careful not to indulge in ‘conspiracy’ claims the alarmists are so fond off.
What this article does seem to miss out is the way the area of climate ‘science’ has seen massive growth of the back of ‘the cause ‘ . From a poor relation to the physical sciences , little heard off and less cared about , it’s become an academic ‘star’ with lots of research cash and positions a plenty . For some it is that which as to be defended to the death, for they know that once the academic ‘trend’ slips away from them, they have nothing but to go back to but obscurity, defunding and lack of jobs.
Can anyone see people like Mann get any role in academic without ‘the cause ‘? So all they can do is keep doubling down in the hope to keep the gravy train on track , and facts be dammed.
This is plain to see by everyone other than the unconvertible zealots. For them, a few other standard techniques might help: plotting the residuals as a histogram or probability plot, residuals versus predicted value, residuals versus time, and predicted values versus actual values.
But why bother? Anyone can see the model doesn’t fit the data. The residuals would all be positive and diverge over time. I guess the hope of those profiting from the public trough is that the real data will eventually catch up with the model.
If I tried to present a model describing drug stability this bad when filing a new drug with any agency, it would result in a nonapproval.
there is a model that accurately predicts temperatures…no computer needed…just paper and pencil…cheap
“They are mere digital masturbation, and have made their operators blind to the truth”. Perfect. Where else in the world can you get this stuff?!?
Thank you Anthony and thank YOU, my noble lord.
It is so clear that the IPCC are in denial about their models being totally wrong. You would think that normal scientists would be celebrating and drinking cocktails(banana daiquiris perhaps?) in the streets from their test tubes with the news that the “catastrophic” warming had stalled. The continuance of arguing with increasingly insane “evidence” shows they have something to hide. They will NEVER admit the whole thing is a fake to create their Fabian Utopian One World Government(in reality, North Korea without the backing of China) because they know what will happen to them when the s%^t hits the fan and the People learn of their treachery.
Typo? In the face of mounting evidence that global temperature is not responding at (as) ordered,
**That … is why the models are doing such a spectacularly awful job of predicting global temperature – which is surely their key objective. **
Yes, doing an awful job of predicting global temperature is indeed their key objective, so that they can pursue their anti-development and anti-human agenda.
Lord Monckton
I enjoyed reading your piece. There was a recent post which featured a talk given by Dr Essex on this very subject. Your post here affirms the points he was making.
I think you’re a bit hard on the poor modelers. Most of the people building and writing them are just doing a job. Trying perhaps do to the impossible, but I don’t think they should be de-funded for it. I think the real problem is that many of the scientists that use them don’t understand them and therefore attach to much confidence in their projections. Somewhere along the line there are scientists who are promoting what they know – at least now – to be inherently flawed methodologies. Perhaps they should be isolated and exposed for misrepresenting the models.
The models really do grossly overstate warming. Still, it is reasonable to consider all factors which influence average temperatures, the most obvious of which is ENSO. If a modest adjustment is made to account for ENSO, then the rate of warming since 1998 increases to about 0.75C per century. If you believe there are longer term cyclical influences (like the AMO/Atlantic thermohaline circulation rate) then a reasonable conclusion is that some of the rapid warming between 1975 and 1997 was the result of longer term cyclical factors; the flip side of which is that some of the recent slowing in warming was due to the downward side of those same factors.
A plausible “underlying rate” in in the range of 0.11C per decade, which is a bit under half the model projection, and completely consistent with a sensitivity to GHG forcing near half of the model diagnosed 3.2C per doubling. I think it is no coincidence that empirical estimates of 1.6 to 1.8C per doubling.
BTW….Lord Mocnkton
A friend of mine works for hedge fund company. He told me that they employ Oxford and Cambridge math graduates to build financial and economic models. He’s a physics graduate and helps run and maintain them. After years of building very complex models in order to predict the market, these incredibly bright people decided that extrapolating a running average a few days ahead was better at predicting the future than the highly complex models they had built.
I do not really understand most of the technical terms in his explanation for the failure of the models. However, I would submit that if the warmists wish to refute Lord Monckton’s arguments, they had better come up with something better than ad hominem attacks and rages against “Big Oil”.
Good post and nice, explanatory, charts. The linear regressions include very low “r-square” values, 0.000-0.035. If, in my work, I had data that gave r2’s like that, I’d re-examine the data set and experimental technique, because I would consider it to be no correlation. In climate science discussions, on the other hand, seem to ignore this lack of correlation and both sides of the issue divine significance of data that seem to be too noisy to have any good confidence level or much of a decent correlation.
I’m currently involved in an effort to optimize operations of a landfill gas to pipeline gas plant. We are collecting data and doing statistical analyses on the data. R2’s of 0.5 mean we can’t can’t attach much significance to the data. One of the things I don’t understand about climate science is making much of very poor correlations. Should you be using other curve-fitting, y=mx+b doesn’t seem to be overly convincing.
Every kind of modelling or forecast-making is an attempt to predict the future. It always was, still is and always will be impossible. I just cannot understand how anyone could believe that these people could predict future climate. To me, this is quite possibly the most intriguing and entertaining part of the great climate swindle. Just imagine, we have politicians sucking up to IPCC’s saucerers. Even Rasputin couldn’t have done a better job!
“predicting global temperature – which is surely their key objective”
I know some people who have been trying to use the same climate models for trying to predict rainfall.
One guy was telling me they were doing very well (tongue in cheek, I might add), because the model mean was tracking really well with reality.
Thing is, about half the models predict more rain, and half predict less rain. 😉
So to summarize: Lord Monckton did pick the dataset with the lowest, (even negative) trend (RSS) of -0.2 ºC/century since all the other datasets show positive trends between +0.44ºC/century and +0.93 ºC/century. So, yes, RSS was a cherry, because it was the only one that showed (be it statistically insignificant) cooling for 200 months (I know, the warming trends of the others are equally statistically insignificant). It is a pity that he chose RSS, since it gave his opponents ammunition to attack his credibility.
As good as this is, what we really need is some cooling that no one can deny/spin instead of non-warming.
Well, I think you’re forgetting the fact that all of the 163 hottest years on record have occurred in the last 163 years! So there…
Sheffield Chris asked:
“has anybody published a more realistic model output that matches reality?”
Yes, as long as one realises that the best we can do so far is determine the direction of trend rather than the rate of that trend. Internal system variation, especially from the oceans, currently confounds quantification of the rate of any underlying longer term trends.
The fact is that zonal jets with reducing cloudiness result in system warming and meridional jets with greater cloudiness result in system cooling by regulating the proportion of ToA insolation that gets into the oceans to drive the climate system.
That fits all the observations that I am aware of including LIA, MWP, Roman Warm Period et al.
http://www.newclimatemodel.com/new-climate-model/
So we need to start over from that point.
Good of you to take time out of your busy jousting schedule and swing by the Village once again, Sir Christopher, encouraging us and lifting our spirits. Hurrah, I say!
Just one little thing, You Grace. It would help us exceedingly (especially those of more feeble faith than your good self) if you would deign to pencil in on your beautiful graphs, just where you think the global temperatures will go in the next 10, 20, 50 years. This would really help – reinforcing our already firm confidence in you that you actually know what you are talking about. You see, I don’t want to be a sneak, but I’ve heared some disquieting murmurs down on the Village Green along the lines of: ‘mud-slinging, yelling ‘yah boo’ and flicking your fingers at falsehood can only buy you cheap credibility; to really sort out the Lords from the serfs, and slay the Serpent good n’ proper, you have to show that you can predict future global temperature better than them.’
So, please: Show us of what stuff you’re made, and that you’re not afraid to go head to head with these amateurs.